Using Data Visualization to Analyze Data

DA $22\mathrm{.}1$ Data visualization can be used to compare income effects of short$-$term decisions.

For this case, you will use an approach similar to that used in the DA$5\mathrm{.}1$ example. You will help a fast food restaurant evaluate the benefits of installing a kiosk in the lobby to automate customer orders, thus reducing the need for cashiers. This case requires you to compare income statement data for traditional and digital ordering for the restaurant, and then create and analyze a bar chart. Presented here are budgeted income statements for a small fast food restaurant. Traditionally, customers order face$-$to$-$face by telling the cashier the items they wish to purchase. In a digital system, customers order and use a credit or debit card to pay at the kiosk, reducing the need for cashiers. The company is contemplating changing to a digital ordering system with kiosks in the lobby.

Comparative budgeted income statements using traditional and digital ordering are provided here.

Income statement data for a traditional and a digital ordering system

Traditional Digital Ordering

Ordering

Revenue

$$450,000$

$$450,000$

Cost of goods sold

$190,000$

$190,000$

Cashier labor

$84,000$

$19,600$

Other variable costs

$18,000$

$18,000$

Contribution margin

$158,000$

$222,400$

Depreciation

$43,000$

$103,000$

Other fixed costs

$45,000$

$45,000$

Net operating income

$$70,000$

$$74,400$

c$.$ By combining the income statement data with and without the revenue volume changes, it is easier to compare the changes in costs and operating income.

Under which model does net operating income appear to increase more when volume increases? What costs changed to create the effect on operating income?

Briefly explain why this occurs.

d$.$ Identify other factors might you need to consider when increasing volume with a digital versus a traditional face$-$to$-$face ordering system.